Navigating the semantic space: unraveling the structure of meaning in psychosis using different computational language models

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• dc.contributor.author He, Rui
• dc.contributor.author Palominos Flores, Claudio Antonio
• dc.contributor.author Zhang, Han
• dc.contributor.author Alonso-Sánchez, Maria Francisca
• dc.contributor.author Palaniyappan, Lena
• dc.contributor.author Hinzen, Wolfram
• dc.date.accessioned 2024-05-21T09:10:23Z
• dc.date.available 2024-05-21T09:10:23Z
• dc.date.issued 2024
• dc.date.updated 2024-05-21T09:10:23Z
• dc.description Includes supplementary materials for the online appendix.
• dc.description.abstract Speech in psychosis has long been ascribed as involving `loosening of associations'. We pursued the aim to elucidate its underlying cognitive mechanisms by analysing picture descriptions from 94 subjects (29 healthy controls, 18 participants at clinical high risk, 29 with first-episode psychosis, and 18 with chronic schizophrenia), using five language models with different computational architectures: FastText, which represents meaning non-contextually/statically; BERT, which represents contextual meaning sensitive to grammar and context; Infersent and SBERT, which provide sentential representations; and CLIP, which evaluates speech relative to a visual stimulus. These models were used to quantify semantic distances crossed between successive tokens/sentences, and semantic perplexity indicating unexpectedness in continuations. Results showed that, among patients, semantic similarity increased when measured with FastText, Infersent, and SBERT, while it decreased with CLIP and BERT. Higher perplexity was observed in first-episode psychosis. Static semantic measures were associated with clinically measured impoverishment of thought and referential semantic measures with disorganization. These patterns indicate a shrinking conceptual semantic space as represented by static language models, which co-occurs with a widening in the referential semantic space as represented by contextual models. This duality underlines the need to separate these two forms of meaning for understanding mechanisms involved in semantic change in psychosis.
• dc.description.sponsorship This research was supported by the Ministerio de Ciencia, Innovación y Universidades (MCIU) and the Agencia Estatal de Investigación (AEI) (grant PID2019-105241GB-I00/AEI/10.13039/501100011033 to WH), the grant TRUSTING, HORIZON-HLTH-2022-STAYHLTH-01, grant nr. 101080251-2 (to WH), China Scholarship Council (grant 202108390062 to RH), the Department of Science and Technology of Guangdong Province (grant 112175605105 to WH and RH), and the National Agency for Research and Development (ANID), Scholarship Program, Becas Chile 2019, Postdoctoral Fellow 74200048 (MA) (to MFAS). The data acquisition for this study was funded by CIHR Foundation Grant (FDN 154296) to LP and was supported by the Canada First Excellence Research Fund to BrainSCAN, Western University (Imaging Core); Innovation fund for Academic Medical Organization of Southwest Ontario; Bucke Family Fund, The Chrysalis Foundation and The Arcangelo Rea Family Foundation (London, Ontario). Compute Canada Resources (Application no. 1530) were used in the storage and analysis of imaging data. LP acknowledges research support from the Canada First Research Excellence Fund, awarded to the Healthy Brains, Healthy Lives initiative at McGill University (New Investigator Supplement); Monique H. Bourgeois Chair in Developmental Disorders and Graham Boeckh Foundation (Douglas Research Centre, McGill University) and a salary award from the Fonds de recherche du Quebec-Sante' (FRQS).
• dc.format.mimetype application/pdf
• dc.identifier.citation He R, Palominos C, Zhang H, Alonso-Sánchez MF, Palaniyappan L, Hinzen W. Navigating the semantic space: unraveling the structure of meaning in psychosis using different computational language models. Psychiatry research. 2024 Mar;333:115752. DOI: 10.1016/j.psychres.2024.115752
• dc.identifier.doi http://dx.doi.org/10.1016/j.psychres.2024.115752
• dc.identifier.issn 0165-1781
• dc.identifier.uri http://hdl.handle.net/10230/60203
• dc.language.iso eng
• dc.publisher Elsevier
• dc.relation.ispartof Psychiatry research. 2024 Mar;333
• dc.relation.projectID info:eu-repo/grantAgreement/ES/2PN/PID2019-105241GB-I00
• dc.relation.projectID info:eu-repo/grantAgreement/EC/HE/101080251
• dc.rights © 2024 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by-nc/4.0/
• dc.subject.keyword Connected speech
• dc.subject.keyword Incoherence
• dc.subject.keyword Semantic similarity
• dc.subject.keyword Semantic perplexity
• dc.subject.keyword Language model
• dc.subject.keyword Loosening of associations
• dc.subject.keyword Schizophrenia
• dc.title Navigating the semantic space: unraveling the structure of meaning in psychosis using different computational language models
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion